BAML

(Bank of America) - letizia.pepe@baml.com - piers.thompson@bankofamerica.com (bounce - user unknown)

Trading Trends

Global real-time information rules the financial markets. Institutions need to make use of complex modelling tools to predict trends and stay ahead of the curve. However, it's currently very difficult to get access to this information without a subscription to various services (e.g. Bloomberg).

With the abundance of data on the web, we now think that there is an opportunity to go outside the usual sources and begin sourcing data from places outside of the norm. For example, as the influence of social networks continues to increase, so does the likelihood of stories and individuals influencing global markets on a more regular basis. Think how a possible tweet from a high profile celebrity may adversely affect the stock price of a certain consumer product, for instance.

The goal of this project is to create a system that models the impact of various sites on financial trends. The system will update itself with information on financial markets and then detect the trends between this data and various news sources. It should potentially look to gather data from a variety of different sources, and build out a model that represents the relations between stories and financial information, presenting it for the user to browse.

Some areas we would consider thinking about are: how you model the data both financially and news related, how you store the scraped data, how to identify a tolerance for variations and the ability to allow a user to specify their own data source.